An emotion assessment of stroke patients by using bispectrum features of EEG signals

• Main Authors: Yean, Choong Wen, Wan Khairunizam Wan Ahmad, Wan Azani Mustafa, Murugappan, Murugappan, Rajamanickam, Yuvaraj, Abdul Hamid Adom, Mohammad Iqbal Omar, Zheng, Bong Siao, Ahmad Kadri Junoh, Zuradzman Mohamad Razlan, Shahriman Abu Bakar
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Emotion; Stroke
• Online Access: https://hdl.handle.net/10356/146181
• Institution: Nanyang Technological University

Emotion assessment in stroke patients gives meaningful information to physiotherapists to identify the appropriate method for treatment. This study was aimed to classify the emotions of stroke patients by applying bispectrum features in electroencephalogram (EEG) signals. EEG signals from three grou...